Automated data provider systems are used to provide data such as stock quotes and bank balances to users over phone lines. The information provided by these automated systems typically comprises two parts. The first part of the information is known as static data. This can be, for example, a standard greeting or prompt, which may be the same for a number of users. The second part of the information is known as dynamic data. The name of the company and the current stock price are dynamic data in the real world, because they change continuously as the users of the automated data provider systems make their selections and prices fluctuate.
The automated data provider systems need to be tested at two levels. One level of testing is to test the static data provided by the automated data provider. This can be accomplished by, for example, testing the voice prompts that guide the user through the menus, ensuring that the correct prompts are presented in the correct order. A second level of testing is to test that the dynamic data reported to the user is correct, for example, that the reported stock price is actually the price for the named company at the time reported.
In existing test systems used to test automated data provider systems, the speech data must be presented to the test system in a training phase prior to the testing phase, which prepares the system to recognize the same speech utterances when presented during the testing phase. The recognition scheme is generally known as discrete speaker dependent speech recognition. Thus, the system is limited to testing speech utterances presented to it a priori, and it is impractical to recognize dynamically changing utterances except where the set of all possible utterances is small.
One system that utilizes speech recognition as part of its provision of testing is the HAMMER IT(trademark) test system available from Empirix Inc. of Wilmington, Mass. The HAMMER IT test system recognizes the responses from the system under test and verifies that the received responses are the responses expected from the system under test. This test system works extremely well for recognizing static responses and for recognizing a limited number of dynamic responses which are known by the test system, however the HAMMER IT currently cannot test for a wide variety of dynamic responses which are unknown by the test system.
Another test system is available from Interactive Quality Systems (IQS) of Hopkins, Minn., utilizes an alternative recognition scheme, namely, length of utterance, but is still limited to recognizing utterances presented to it a priori. It would seem difficult for this system to recognize typical dynamic data, such as numbers, since the utterance xe2x80x9cone two threexe2x80x9d would often have the same duration as the utterance xe2x80x9ctwo one threexe2x80x9d, xe2x80x9cthree two onexe2x80x9d and so on, particularly if the utterances were generated by an automated system.
A possible alternative would be a semi-automated system, in which the dynamic portion of the utterance would be recorded and presented to a human operator for encoding. The dynamic portion of the utterance would be recorded and presented to a human operator for encoding in machine-readable characters.
It would be desirable to have a test system that tests the responses of automated data provider systems which presents both static data and dynamic data. It would be further desirable to have a test system which does not need to know beforehand the possible dynamic data.
With the foregoing background in mind, it is an object of the present invention to provide a method to automate the validation of dynamic data presented over telecommunications paths. The invention utilizes continuous speaker-independent speech recognition together with a process known generally as natural language recognition to reduce dynamic utterances to machine encoded text without requiring a prior training phase. Further, when configured by the end user to do so, the test system will convert common examples of dynamic speech, such as numbers, dates, times, and currency utterances into their usual textual representation. For instance, it will convert the utterance xe2x80x9cfour hundred fifty four dollars and twenty nine centsxe2x80x9d into the more usual representation of xe2x80x9c454.29xe2x80x9d. This will eliminate the limitation that all tested utterances need to be known by the test system in advance of the test.
By converting the dynamic utterances to machine encoded text, the invention facilitates automated validation of the data so converted, by allowing its use as input into an automated system which can independently access and validate the data.